BackgroundMesenchymal stem cells (MSCs) are multipotent stem cells that can be isolated and expanded from many tissues, and are being investigated for use in cell therapies. Though MSC therapies have demonstrated some success, none have been FDA approved for clinical use. MSCs lose stemness ex vivo, decreasing therapeutic potential, and face additional barriers in vivo, decreasing therapeutic efficacy. Culture optimization and genetic modification of MSCs can overcome these barriers. Viral transduction is efficient, but limited by safety concerns related to mutagenicity of integrating viral vectors and potential immunogenicity of viral antigens. Nonviral delivery methods are safer, though limited by inefficiency and toxicity, and are flexible and scalable, making them attractive for engineering MSC therapies.Main textTransfection method and nucleic acid determine efficiency and expression profile in transfection of MSCs. Transfection methods include microinjection, electroporation, and nanocarrier delivery. Microinjection and electroporation are efficient, but are limited by throughput and toxicity. In contrast, a variety of nanocarriers have been demonstrated to transfer nucleic acids into cells, however nanocarrier delivery to MSCs has traditionally been inefficient. To improve efficiency, plasmid sequences can be optimized by choice of promoter, inclusion of DNA targeting sequences, and removal of bacterial elements. Instead of DNA, RNA can be delivered for rapid protein expression or regulation of endogenous gene expression. Beyond choice of nanocarrier and nucleic acid, transfection can be optimized by priming cells with media additives and cell culture surface modifications to modulate barriers of transfection. Media additives known to enhance MSC transfection include glucocorticoids and histone deacetylase inhibitors. Culture surface properties known to modulate MSC transfection include substrate stiffness and specific protein coating. If nonviral gene delivery to MSCs can be sufficiently improved, MSC therapies could be enhanced by transfection for guided differentiation and reprogramming, transplantation survival and directed homing, and secretion of therapeutics. We discuss utilized delivery methods and nucleic acids, and resulting efficiency and outcomes, in transfection of MSCs reported for such applications.ConclusionRecent developments in transfection methods, including nanocarrier and nucleic acid technologies, combined with chemical and physical priming of MSCs, may sufficiently improve transfection efficiency, enabling scalable genetic engineering of MSCs, potentially bringing effective MSC therapies to patients.

Human mesenchymal stem cells (hMSCs) are under intense study for applications of cell and gene therapeutics because of their unique immunomodulatory and regenerative properties. Safe and efficient genetic modification of hMSCs could increase their clinical potential by allowing functional expression of therapeutic transgenes or control over behavior and differentiation. Viral gene delivery is efficient, but suffers from safety issues, while nonviral methods are safe, but highly inefficient, especially in hMSCs. Our lab previously demonstrated that priming cells before delivery of DNA complexes with dexamethasone (DEX), an anti‐inflammatory glucocorticoid drug, significantly increases hMSC transfection success. This work systematically investigates the mechanisms of hMSC transfection and DEX‐mediated enhancement of transfection. Our results show that hMSC transfection and its enhancement by DEX are decreased by inhibiting classical intracellular transport and nuclear import pathways, but DEX transfection priming does not increase cellular or nuclear internalization of plasmid DNA (pDNA). We also show that hMSC transgene expression is largely affected by pDNA promoter and enhancer sequence changes, but DEX‐mediated enhancement of transfection is unaffected by any pDNA sequence changes. Furthermore, DEX‐mediated transfection enhancement is not the result of increased transgene messenger RNA transcription or stability. However, DEX‐priming increases total protein synthesis by preventing hMSC apoptosis induced by transfection, resulting in increased translation of transgenic protein. DEX may also promote further enhancement of transgenic reporter enzyme activity by other downstream mechanisms. Mechanistic studies of nonviral gene delivery will inform future rationally designed technologies for safe and efficient genetic modification of clinically relevant cell types.

The grafting of polymer brushes to substrates is a promising method to modify surface properties such as wettability and the affinity toward proteins and cells for applications in microelectronics, biomedical devices, and sensors. Poly(acrylic) acid (PAA) brushes are of high interest because of their stimuli-responsive behavior and the presence of carboxy (COOH) groups, which allow for immobilization of bioactive molecules. The "grafting-to" approach results in homogeneous and well-defined polymer brushes, but, although grafting-to has been demonstrated with PAA brushes on silicon (Si) substrates, it has not been performed on biocompatible materials such as titanium (Ti). Here, we have described a facile method to modify biocompatible Ti substrates with PAA brushes to amplify their substrate functionality. The grafting-to PAA "pseudo" brushes were successfully grafted to Ti substrates and retained their pH-dependent swelling behavior. An RGD peptide was covalently bound to COOH groups of the PAA brushes (PAA-RGD) as a model bioactive group. While NIH/3T cell adhesion was significantly decreased on PAA-functionalized Ti substrates, PAA-RGD on Ti had cell adhesion comparable to that of flat Ti at 24 and 48 h, with significantly more cells adhered to PAA-RGD compared to PAA on Ti at 48 h.

Nonviral gene delivery methods are advantageous over viral vectors in terms of safety, cost, and flexibility in design and application, but suffer from lower gene transfer efficiency. In addition to modifications to nucleic acid design and nonviral carriers, new tools are sought to enhance transfection. Priming is the pharmacological modulation of transfection efficiency and transgene expression, and has demonstrated transfection increase in several compounds, for example, chloroquine and glucocorticoids. To develop a library of transfection priming compounds, a high‐throughput screen was performed of the NIH Clinical Collection (NCC) to identify clinical compounds that prime polyethylenimine (PEI) transfection. HEK293T cells were treated with priming compounds, then transfected with enhanced green fluorescent protein (EGFP)‐encoding plasmid by PEI. After 48‐hr culture, primed and transfected cells were assayed for transfection, cell proliferation, and cell viability by fluorescence measurement of EGFP reporter, Hoechst 33342 nuclei stain, and resazurin metabolic assay. From the microscope image analysis and microplate measurements, transfection fold‐changes were determined, and compounds resulting in statistically significant transfection fold‐change were identified. NCC compounds were clustered using PubChem fingerprint similarity by Tanimoto coefficients in ChemmineTools. Fold‐changes for each compound were linked to drug clusters, from which drug classes that prime transfection were identified. Among the identified drugs classes that primed transfection increases were antioxidants, GABAA receptor modulators, and glucocorticoids. Resveratrol and piceid, stilbenoid antioxidants found in grapes, and zolpidem, a GABAA modulator, increased transfection nearly three‐fold. Literature indicate interaction of the identified transfection priming drug clusters with mitochondria, which may modulate mitochondrial dysfunction known to be associated with PEI transfection.

Background: Human mesenchymal stem cells (hMSCs) are intensely researched for applications in cell therapeutics due to their unique properties, however, intrinsic therapeutic properties of hMSCs could be enhanced by genetic modification. Viral transduction is efficient, but suffers from safety issues. Conversely, nonviral gene delivery, while safer compared to viral, suffers from inefficiency and cytotoxicity, especially in hMSCs. To address the shortcomings of nonviral gene delivery to hMSCs, our lab has previously demonstrated that pharmacological 'priming' of hMSCs with the glucocorticoid dexamethasone can significantly increase transfection in hMSCs by modulating transfectioninduced cytotoxicity. This work seeks to establish a library of transfection priming compounds for hMSCs by screening 707 FDA-approved drugs, belonging to diverse drug classes, from the NIH Clinical Collection at four concentrations for their ability to modulate nonviral gene delivery to adipose-derived hMSCs from two human donors. Results: Microscope images of cells transfected with a fluorescent transgene were analyzed in order to identify compounds that significantly affected hMSC transfection without significant toxicity. Compound classes that increased transfection across both donors included glucocorticoids, antibiotics, and antihypertensives. Notably, clobetasol propionate, a glucocorticoid, increased transgene production 18-fold over unprimed transfection. Furthermore, compound classes that decreased transfection across both donors included flavonoids, antibiotics, and antihypertensives, with the flavonoid epigallocatechin gallate decreasing transgene production − 41-fold compared to unprimed transfection. Conclusions: Our screen of the NCC is the first high-throughput and drug-repurposing approach to identify nonviral gene delivery priming compounds in two donors of hMSCs. Priming compounds and classes identified in this screen suggest that modulation of proliferation, mitochondrial function, and apoptosis is vital for enhancing nonviral gene delivery to hMSCs.

e16265 Background: Pancreatic cancer (PaCa) is the third leading cause of cancer death in the United States despite its low incidence rate, owing to a 5-year survival rate of 10%. It is often asymptomatic in early stage, resulting in the majority of diagnoses occurring when cancer has already metastasized to distant organs. Late diagnosis deprives patients of potentially curative treatments such as surgery and impacts survival rates. Diabetes can be an early symptom of PaCa. Indeed, 25% of PaCa patients had a preceding diabetes diagnosis. Among all people with new onset diabetes (NOD), 0.85% will be diagnosed with PaCa within 3 years, which represents 6-8 fold increased risk for PaCa compared to the general population. Surveillance of the NOD population for PaCa presents an opportunity to shift PaCa diagnosis to earlier stage by finding it sooner. Methods: Whole blood was obtained from a cohort of 117 PaCa patients as well as 800 non-cancer controls with and without NOD. Plasma was processed to isolate cfDNA and 5hmC and low pass whole genome libraries were generated and sequenced. The EpiDetect assay combines 5hmC and whole genome sequencing data and were generated using Bluestar Genomics’s technology platform. Results: To investigate whether PaCa can be detected in plasma, we interrogated plasma-derived cfDNA epigenomic and genomic signal from PaCa patients and non-cancer controls. We first trained stacked ensemble models on PaCa and non-cancer samples utilizing 5hmC, fragmentation and CNV-based biomarkers from cfDNA. These models performed stably with a median of 72.8% sensitivity and 90.1% specificity measured across 25 outer fold iterations using the training data set, which was composed of 50% early stage (Stages I & II) disease. The final binomial ensemble model was trained using all of the training data, yielding an area under the receiver operating characteristic curve (auROC) of 0.9, with 75% sensitivity and 89% specificity. This model was then tested on an independent validation data set from 33 PaCa patients (24 with diabetes, 15 of which was NOD) and 202 non-cancer control patients (76 with diabetes, 51 of which was NOD) and yielded a classification performance auROC of 0.9 with 67% sensitivity at 92% specificity. Lastly, model performance in the subset of patient cohort with NOD only had an auROC of 0.87 with 60% sensitivity at 88% specificity. Conclusions: Our results indicate that 5hmC profiles along with CNV and fragmentation patterns from cfDNA can be used to detect PaCa in plasma-derived cfDNA. Overall, model performance was stable and consistent between the training and independent validation datasets. A larger clinical study is under development to investigate the utility of the model described in this pilot study in identifying occult PaCa within the NOD population, with the aim of shifting diagnosis to early stage and potentially improving patient outcomes.

1539 Background: Epigenomic changes in DNA methylation patterns are more precisely delineated by active demethylation events as marked by 5-hydroxymethylation (5hmC) of cytosine residues. 5hmC appears to be dynamically modulated in tumor tissues and can be employed as a cancer biomarker. Strategies which interrogate 5hmC genome-wide patterns in a liquid biopsy context may provide efficient and precise technology for early cancer screening and detection. In this study we identified genome-wide 5hmC changes in plasma based circulating free DNA (cfDNA) from breast, colorectal, lung, pancreatic and prostate cancer patients versus non-cancer individuals. Methods: cfDNA was isolated from plasma, enriched for the 5hmC fraction using novel click-chemistry protocol for labelling followed by sequencing and alignment to a reference genome to construct features sets of 5hmC patterns. Regularized classification models were constructed to classify cancer samples apart from non-cancer. Results: > 500 non-cancer individuals and > 500 cancer patients across five cancer types (breast, colorectal, lung, pancreas and prostate) were included in this study. About 60% of the cancer samples were early stage disease (I or II). The ability to classify non-cancer versus cancer patients was evaluated by 5-fold cross validation of our trained prediction models. Our models were able to classify all breast cancer with a test auROC of 0.86 while prediction model classification for ER negative samples had an auROC of 0.92. Colorectal performance auROC was 0.9; lung auROC = 0.92, pancreatic auROC = 0.97 and prostate auROC = 0.91. Overall sensitivity range, when allowing 2% false positive, was between 85% and 52%. Further using 5hmC signal in blood we were able to identify several signaling pathways specifically relevant to the biology of the cancers investigated. Conclusions: These findings further demonstrate that 5hmC changes in cfDNA enable non-invasive detection of breast, colorectal, lung pancreatic, and prostate cancers. Further, 5hmC signals enabled the identification of a suite of cancer signaling pathways differentially enriched in cancers versus non-cancers. These data suggest that dynamic changes in tumor cell methylation, detectable through 5-hydroxymethylation, are contained in the circulating blood and signal active disease biology.

3044 Background: Epigenomics assays have recently become popular tools for identification of molecular biomarkers, both in tissue and in plasma. In particular 5-hydroxymethyl-cytosine (5hmC) method, has been shown to enable the epigenomic regulation of gene expression and subsequent gene activity, with different patterns, across several tumor and normal tissues types. In this study we show that 5hmC profiles enable discrete classification of tumor and normal tissue for breast, colorectal, lung ovary and pancreas. Such classification was also recapitulated in cfDNA from patient with breast, colorectal, lung, ovarian and pancreatic cancers. Methods: DNA was isolated from 176 fresh frozen tissues from breast, colorectal, lung, ovary and pancreas (44 per tumor per tissue type and up to 11 tumor tissues for each stage (I-IV)) and up to 10 normal tissues per tissue type. cfDNA was isolated from plasma from 783 non-cancer individuals and 569 cancer patients. Plasma-isolated cfDNA and tumor genomic DNA, were enriched for the 5hmC fraction using chemical labelling, sequenced, and aligned to a reference genome to construct features sets of 5hmC patterns. Results: 5hmC multinomial logistic regression analysis was employed across tumor and normal tissues and identified a set of specific and discrete tumor and normal tissue gene-based features. This indicates that we can classify samples regardless of source, with a high degree of accuracy, based on tissue of origin and also distinguish between normal and tumor status.Next, we employed a stacked ensemble machine learning algorithm combining multiple logistic regression models across diverse feature sets to the cfDNA dataset composed of 783 non cancers and 569 cancers comprising 67 breast, 118 colorectal, 210 Lung, 71 ovarian and 100 pancreatic cancers. We identified a genomic signature that enable the classification of non-cancer versus cancers with an outer fold cross validation sensitivity of 49% (CI 45%-53%) at 99% specificity. Further, individual cancer outer fold cross validation sensitivity at 99% specificity, was measured as follows: breast 30% (CI 119% -42%); colorectal 41% (CI 32%-50%); lung 49% (CI 42%-56%); ovarian 72% (CI 60-82%); pancreatic 56% (CI 46%-66%). Conclusions: This study demonstrates that 5hmC profiles can distinguish cancer and normal tissues based on their origin. Further, 5hmC changes in cfDNA enables detection of the several cancer types: breast, colorectal, lung, ovarian and pancreatic cancers. Our technology provides a non-invasive tool for cancer detection with low risk sample collection enabling improved compliance than current screening methods. Among other utilities, we believe our technology could be applied to asymptomatic high-risk individuals thus enabling enrichment for those subjects that most need a diagnostic imaging follow up.